The vulnerability identified as CVE-2026-27025 affects the pypdf library, a widely used open-source pure-Python PDF processing tool. The issue arises from excessive iteration when parsing the /ToUnicode entry of fonts within a PDF document. An attacker can craft a malicious PDF containing unusually large or complex /ToUnicode mappings, which causes the pypdf parser to consume excessive CPU time and memory during text extraction operations. This leads to denial of service (DoS) conditions by significantly degrading performance or exhausting system resources. The vulnerability exists in all pypdf versions prior to 6.7.1 and does not require any privileges, authentication, or user interaction to exploit. The CVSS 4.0 base score is 6.9, reflecting a medium severity primarily due to the local attack vector and lack of direct confidentiality or integrity impact. The flaw is classified under CWE-834 (Excessive Iteration), indicating inefficient or uncontrolled looping in code. Although no public exploits have been reported, the vulnerability poses a risk to any system that automatically processes untrusted PDF files using vulnerable pypdf versions. The issue was addressed in pypdf 6.7.1 by likely adding limits or safeguards to the parsing logic of the /ToUnicode font entry to prevent resource exhaustion.

The primary impact of CVE-2026-27025 is denial of service through resource exhaustion. Systems that use vulnerable versions of pypdf to parse or extract text from PDFs can experience significant slowdowns or crashes when processing maliciously crafted files. This can disrupt automated workflows such as document indexing, content extraction, or malware scanning that rely on pypdf. Organizations handling large volumes of PDF documents, especially from untrusted sources, are at risk of service interruptions or degraded performance. While the vulnerability does not directly compromise confidentiality or integrity, the availability impact can affect business continuity and user experience. In environments where PDF processing is part of security controls or data pipelines, this vulnerability could be leveraged as a vector to cause operational disruption. The lack of required authentication or user interaction increases the risk in automated or backend processing scenarios.

To mitigate CVE-2026-27025, organizations should upgrade all instances of the pypdf library to version 6.7.1 or later, where the vulnerability is fixed. For environments where immediate upgrade is not feasible, implementing input validation or sandboxing of PDF processing tasks can reduce risk. Limiting resource allocation (CPU and memory) for PDF parsing processes can help contain potential denial of service effects. Monitoring for unusually high resource consumption during PDF processing and alerting on anomalies can provide early detection. Additionally, restricting the acceptance of PDFs from untrusted or unauthenticated sources reduces exposure. Developers should review and harden any custom PDF parsing code to avoid excessive iteration patterns. Incorporating rate limiting or queuing mechanisms for PDF processing jobs can further mitigate impact. Finally, maintaining an inventory of software dependencies and applying timely security updates is critical to prevent exploitation.